74 research outputs found
Data privacy in knowledge discovery
No full textThis thesis addresses data privacy in various stages of extracting knowledge embedded in databases. Advances in computer networking and database technologies have enabled the collection and storage of vast quantities of data. Legal and ethical considerations might require measures to protect an individual's privacy in any use or release of the data. In this thesis, we address the problem of preserving privacy in the two following cases: (1) in distributed knowledge discovery; (2) in situations where the output of a data mining algorithm could itself breach privacy. We present results in two different models, namely secure multiparty computation (SMC) and differential privacy. The first part of the thesis presents privacy preserving protocols in the SMC model. Secure multiparty computation involves the collaborative computation of functions based on inputs from multiple parties. The privacy goal is to ensure that all parties receive only the final output without any party learning anything beyond what can be inferred from the output. Within this framework we address the problem of preserving privacy in the preprocessing and the data mining stages of knowledge discovery in databases. For the preprocessing stage, we present private protocols for the imputation of missing data in a dataset that is shared between two parties. For the data mining stage, we introduce the notion of arbitrarily partitioned data that generalizes both horizontally and vertically partitioned data. We present a privacy-preserving protocol for k-means clustering of arbitrarily partitioned data. We also develop a new simple k-clustering algorithm that was designed to be converted into a communication-efficient protocol for private clustering. The second part of the thesis deals with privacy in situations where the output of a data mining algorithm could itself breach privacy. In this setting, we present private inference control protocols in the SMC model for On-line Analytical Processing systems. In the differential privacymodel, the goal is to provide access to a statistical database while preserving the privacy of every individual in the database, irrespective of any auxiliary information that may be available to the database client. Under this privacy model, we present a practical privacy preserving decision tree classifier using random decision trees.Ph.D.Includes abstractVitaIncludes bibliographical referencesby Geetha Jagannatha
A dangerous but powerful idea - counter acceleration and speed with slowness and wholeness
No full textThe dangerous idea is that school reform, in India in particular, but across the world too, is impossible. Changing education, at the systemic level or at the institutional or school level, or educating teachers and school leaders in change can be classified as largely first order change - that of school improvement, which involves doing more of the same but doing it better (where the focus is on efficiency) and that of school re-structuring, which involves re-organising components and responsibilities (where the focus is on effectiveness). Geetha Narayanan is Principal Investigator with Project Vision at the Centre for Education Research Training and Development (CERTAD) within the Srishti School of Art Design and Technology in Bangalore, India. She has dedicated her career to finding and establishing new models of education that are creative, synergistic and original in their approach to learning. Read the article and listen to audio of the author discussing her ideas
Tetranchyroderma hystrix Remane 1926
No full textTetranchyroderma hystrix Remane, 1926 Records from India. KERALA: Neendakara—Rajan & Nair (1979). Habitat. It has been recorded in well sorted sand with grain size ranging mostly from 295 to 592 µm Remarks. This species has been recorded by Rajan & Nair (1979) from Kerala in their ecological work, along with other gastrotrichs species and meiofauna. There is no drawing and other taxonomic data of this species provided by them or any other author from India. Consequently, we consider this species finding as a doubtful record that require more evidence to prove the presence of this species on the Indian coast.Published as part of Chatterjee, Tapas, Priyalakshmi, Geetha & Todaro, M. Antonio, 2019, An annotated checklist of the macrodasyidan Gastrotricha from India, pp. 495-510 in Zootaxa 4545 (4) on page 503, DOI: 10.11646/zootaxa.4545.4.3, http://zenodo.org/record/261830
Abstractive and extractive based YouTube transcript summarization: a hybrid approach
No full textThe rapid advancement in the field of communication and ubiquitous access to computing has led to the proliferation of large amounts of video content on YouTube and other social media platforms. However, getting precise information from the video in concise textual manner remains a challenge. Different extractive and abstractive text summarization methods are prevalent in the literature. In this paper, classical extractive text summarization methods Luhn’s algorithm, TextRank algorithm and Keyword- based summarization are combined to develop a combined extractive (CE) method. To enhance its performance, bidirectional and auto-regressive transformers (BART) is investigated and integrated as a hybrid model. Further, we explore how Kmeans clustering algorithm can be used for text summarization in general and with the proposed hybrid approach for improvement in text summarization. Using CNN/DailyMail dataset, assessment of text summarization methods based on ROUGE scores and time taken for summary generation is carried out. Based on the ROUGE score, we observe that the proposed hybrid method - 0.2644 is better than traditional extractive summarization methods. The combination of hybrid method with K-means further improved the score to 0.3227. The time taken by them for summary generation are 138.09 and 142.16 seconds respectively. This work experimented with different classical and transformer-based text summarization techniques to explore the complementary aspects and the results obtained are comparable with that of existing models with less time for text summarization
Tie-Simplex Parameterization of Operator Based Linearization for Isothermal Multiphase Compositional Flow In Porous Media
No full textCompositional flow simulation is the best practise to model the complex enhanced oil recovery process. This involves solving highly coupled and non linear flow, transport equations.Interaction of components within different phases and the fluid interaction with rock properties makes it difficult to accurately predict the natural flow process in the reservoir. Thisdemands for resolution models and accurate representation of flow process with realistic assumptions., which is quite challenging with conventional simulation.The newly proposed Operator based linearization (OBL) approach handles the problem in adifferent way. Governing equations are regrouped using state and space operators. The stateoperators are computed at the nodes of uniform mesh in parameter space and multi- linearinterpolation is performed during simulation. Uniformly distributed supporting points ignorethe underlying physics leading to higher interpolation error around the phase boundary anddemanding higher resolution to achieve the desired accuracy.The objective of “Tie simplex parameterization of Operator-Based Linearization for IsothermalMultiphase Compositional flow in porous media” is to parameterize the compositional spaceby accounting the underlying physics. A set of tie lines captures the phase boundary inparameter space at given pressure and temperature. Tessellation is performed by extendingthe tie lines to the entire compositional space. The supporting points are assigned along theextended tie-lines according to manually designed heuristics. After that, the parameterizedspace is tessellated further using Delaunay triangulation, and barycentric interpolation isperformed within each simplex.The efficiency of the developed approach is demonstrated in comparison with the uniformparameterization using 1D displacement of compositional two-phase fluid. The convergenceof non linear newton iterative solver is studied by applying the OBL framework with newlyproposed interpolation and existing Multi-Linear interpolation framework.Operator-Based LinearizationPetroleum Engineering and Geo-science
Transformation of Fusarium
No full textThis Dissertation / Report is the outcome of investigation carried out by the creator(s) / author(s) at the department/division of Central Food Technological Research Institute (CFTRI), Mysore mentioned below in this page
Molecular characterization of native isolate of bacteriocin producing Pediococcus pentosaceus CFR III
No full textThis Dissertation / Report is the outcome of investigation carried out by the creator(s) / author(s) at the department/division of Central Food Technological Research Institute (CFTRI), Mysore mentioned below in this page
Isolation of Bioactive Compounds from Phyllanthus Emblica (Indian Gooseberry)
No full textThis Dissertation / Report is the outcome of investigation carried out by the creator(s) / author(s) at the department/division of Central Food Technological Research Institute (CFTRI), Mysore mentioned below in this page
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